Election Prediction Using Sentiment Analysis

Abstract

Opinion identification is an important objective, especially for election candidates, using social networking sites. One can obsequies a common trend among individuals in terms of likeness or dis-likeness. This forms the basis of our project where we performed sentiment analysis on data acquired from Twitter. Hence, we analyzed tweets and measured where they can be termed as negative, positive, or neutral. We have focused on estimating likeness for the people in California and other selected States. This application can help in scenarios where a large number of participants are required. The application gives you a clear picture beforehand of what can be expected.Our main area will be to target California and other selected states. 55 seat data will be collected and the hashtags that are more trending at that time will be looked over to make better predictions about the result